Rapid monitoring of SARS-CoV-2 variants of concern through high-resolution melt analysis

The current global pandemic of COVID-19 is characterized by waves of infection due to the emergence of new SARS-CoV-2 variants carrying mutations on the Spike (S) protein gene. Since autumn 2020 many Variants of Concern (VOC) have been reported: Alpha/B.1.1.7, Beta/B.1.351, Gamma/P.1, Delta/B.1.617.2, Omicron/B.1.1.529, and sublineages. Surveillance of genomic variants is currently based on whole-genome sequencing (WGS) of viral genomes on a random fraction of samples positive to molecular tests. WGS involves high costs, extended analysis time, specialized staff, and expensive instruments compared to a PCR-based test. To rapidly identify the VOCs in positive samples, six assays based on real-time PCR and high-resolution melting (HRM) were designed on the S gene and applied to 120 oro/nasopharyngeal swab samples collected from October 2020 to June 2022 (106 positive and 14 negative samples). Overall, the assays showed 100% specificity and sensitivity compared with commercial PCR tests for COVID-19. Moreover, 104 samples out of 106 (98.1%) were correctly identified as follows: 8 Wuhan (wild type), 12 Alpha, 23 Delta, 46 Omicron BA.1/BA.1.1, 15 Omicron BA.2/BA.4/BA.5. With our lab equipment, about 10 samples can be processed every 3 h at the cost of less than € 10 ($ 10.60) per sample, including RNA extraction. The implementation of this approach could help local epidemiological surveillance and clinical decision-making.

Currently, whole-genome sequencing (WGS) is employed for the characterization of SARS-CoV-2 variants worldwide, and millions of sequences have been recorded in public databases, such as the Global Initiative on Sharing All Influenza Data (GISAID) 8 or GenBank.The WGS not only requires a long time of processing and professional expertise for data analysis, but it is also expensive in terms of equipment and reagents.Reverse transcription real-time PCR (RT-qPCR) could be a rapid method for the identification of VOCs 9 .In particular, an approach based on real-time PCR coupled with high-resolution melting (HRM) analysis could be considered a faster and cheaper alternative to the WGS 10,11 .In fact, in the last decades, the HRM analysis employing saturating or non-saturating DNA intercalating dyes has gained increasing interest due to its ability to monitor mutations and genotyping in many research fields, such as epidemiology and microbiology.For example, the use of HRM analysis has previously been widely applied for detecting bacteria and antimicrobial resistance genes 12,13 , genotyping protozoan parasites such as Plasmodium falciparum 14 and Leishmania spp. 15,16, testing drug susceptibility in influenza A viruses 17 , testing drug resistance in hepatitis B virus 18 , and studying HIV diversity 19 .
In this work, we describe the development and assessment of a rapid, cost-effective method based on HRM analysis to detect SARS-CoV-2 VOCs in a routine clinical setting.The SARS-CoV-2 Spike protein-coding region PCR amplicons are identified by unique mutation signatures, such as single nucleotide polymorphisms (SNPs) and deletions, with the aim to detect VOCs without the need for labeled probes.The method relies on the use of a versatile diagnostic algorithm that could be adapted depending on circulating variants.

Evaluation of RT-qPCR assays sensitivity and specificity
Primer specificity was first checked in silico either with human genome or with common human coronaviruses (i.e., Alpha coronavirus 229E, NL63; Beta coronavirus OC43, HKU1).After amplification from oro/nasopharyngeal swab samples, selected PCR products were analyzed by agarose gel electrophoresis showing bands at the expected size and the absence of non-specific products or primer dimers (Supplementary Fig. 2).All positive and negative results obtained with commercial IVD-certified molecular tests were confirmed with the qPCR assays described in this paper, accounting for 100% specificity and sensitivity of our assays.The Ct values in our assays were < 30 in 105 out of 106 positive samples.The analytical sensitivity was tested using SARS-CoV2 synthetic RNA of the reference isolate Wuhan-hu-1 as described in methods.The linear limit of detection of all assays was 1 × 10 2 viral genome copies/reaction tube (with or without background host RNA), except for assay 2930-3100, which showed a sensitivity of 1 × 10 3 viral genome copies/reaction tube (Supplementary Fig. 3).Moreover, all assays were tested by qPCR to evaluate the specificity using RNA from 10 clinical specimens positive for common respiratory viruses and 4 DNA samples extracted from colonies of respiratory pathogen bacteria, as described in methods.PCR mixtures were analyzed by agarose gel electrophoresis, confirming the absence of cross-reactivity with these pathogens (Supplementary Fig. 4).The amplifiability of RNA from clinical specimens positive for other respiratory viruses was confirmed using a commercial IVD-certified kit for differential diagnosis of infections by SARS-CoV-2, Influenza A, Influenza B and Respiratory Syncytial Virus A/B, which included RNase P gene as endogenous control.The results confirmed the positivity of those samples and their amplifiability (Supplementary Table 1).

SARS-CoV-2 VOCs discrimination
A total of 120 oro/nasopharyngeal swab samples collected from October 2020 to June 2022 (106 positive samples and 14 negative samples) were used to validate our assays.
These assays can be performed hierarchically in a diagnostic algorithm (Fig. 2).Through this approach we were able to discriminate the main VOCs circulating by the time of writing this manuscript.For example, within the Omicron variants, the hierarchical approach "OMICRON CA" followed by "DEL9" allows to distinguish the three clusters [BA.1/BA.1.1],[BA.3] and [BA.2/BA.4/BA.5].The results were confirmed by PCR product sequencing and/or by the available WGS data.Positive percent agreement (sensitivity) and negative percent agreement (specificity) for each assay, using sequencing as the reference method, are reported in Table 4.
All data are resumed in Supplementary Table 2.In summary, the qPCR assays followed by HRM analysis allowed to assign the correct VOC in all positive samples, with the exception of two samples (20044, 49095).Sample 20044 was tested with two qPCR assays (SC2DELTAnew and OMICRON CA), but in this case, the HRM profiles did not allow to assign a genotype.In fact, the PCR products sequencing showed the presence of two possible amplicons: with and without 467/472 deletion, and with and without C2568A mutation for qPCR assay SC2DELTAnew and OMICRON CA, respectively (Supplementary Fig. 5).Sample 49095 was tested with qPCR assays OMICRON CA and DEL9.The HRM analysis assigned this sample to Omicron BA.1/BA.1.1 variant; however, this result did not match with WGS data that indicated Omicron BA.4 variant.

Discussion
As of Autumn 2020, several countries have reported the detection of SARS-CoV-2 variants, characterized by high transmissibility or reduced susceptibility to neutralizing antibodies induced by infection or vaccination 5 .The genome of these variants presents a number of mutations and some are included in the ACE2 binding domain of the Spike protein, increasing the viral binding to host cells [24][25][26][27] .Surveillance of genomic variants, together with compliance with public health measures (vaccination, use of masks, isolation, and quarantine), has been essential to limit the spread of SARS-CoV-2.
Currently, the surveillance of genomic variants is based on the WGS of viral genomes, able to explore the whole SARS-CoV-2 genome in detail 28,29 even though it is performed on a minority fraction of positive samples.However, WGS approaches are characterized by high costs and extended analysis times compared to PCR-based diagnostic tests, and the delay in obtaining WGS results could hinder the public health response and real-time prevalence evaluation of the different variants in the population.As an alternative to WGS, other methods for variant identification have been reported.Very recently, Burgos et al. proposed a method based on PCR amplification of four polymorphic genetic regions coupled with Sanger sequencing 30 .Although this approach has lower costs and time of processing compared to WGS, it is still time-consuming, and it cannot detect new mutations in a region of the viral genome different from those considered for sequencing.Moreover, it requires expensive instrumentation (Sanger sequencing instrument).Among the molecular approaches attempted to simplify the typing process and lower its cost, several qPCR methods based on probes targeting different SARS-CoV-2 mutations have been introduced.For example, Yeung et al. designed and validated a multiplex RT-qPCR assay based on labeled probes targeting Spike protein mutations to detect Alpha, Beta, Gamma, Delta, and Omicron VOCs 31 .The probes increase the specificity of the assay but their use can be expensive and could give false negative   www.nature.com/scientificreports/results in case of mismatches to the targeted site 32 .For these reasons, researchers have started to develop faster, cheaper, and more flexible tests which can be adapted as needed.Our study is centered on the development of a qPCR coupled with HRM analysis for SARS-CoV-2 variants identification.HRM analysis can be used to assess whether two or more PCR products of similar size, amplified by the same primer pair, have identical nucleotide sequence.After the amplification, the PCR products are subjected to small increases in temperature (generally 0.1-0.3°C for 2-10 s) to reach the melting temperature to which the double-stranded amplicon is denatured.Therefore, based on Tm differences, it is possible to determine the presence of mutations (SNPs and indels).This approach is more affordable than a probe-based approach and it has been used widely for typing pathogens, including RNA viruses [33][34][35] .
In the attempt to develop an economical tool for the rapid screening of the main SARS-CoV-2 VOCs, we designed a diagnostic algorithm using six different hierarchical qPCR-HRM assays able to discriminate the main VOCs circulating from the beginning of the pandemic until the time we drafted this manuscript.The choice and the number of assay(s) will be decided by the operator and will be based on the current epidemiological situation.As new variants emerge, the diagnostic algorithm could be updated with novel designed assays.
This approach has proven to be very effective, showing 97.7% agreement with sequencing data (84 out of 86 samples with sequence information).Only samples 20044 and 49095 displayed HRM results that were not confirmed by sequencing data.Concerning sample 20044, as described in the results, the PCR product sequences showed the presence of two amplicons corresponding to Delta and Omicron BA.1/BA.1.1 variants, indicating a possible co-infection, as previously reported 36 .Moreover, it is noteworthy that this sample was collected on December 19th, 2021, when Delta and Omicron variants were co-existing in our territory.Concerning sample 49095, the Ct values of the two qPCR assays used for variant identification (OMICRON CA and DEL9) were both > 30; this delay in amplification could have affected the reliability of HRM analysis, as reported previously [37][38][39] .
The qPCR-HRM assays were tested using two commercial mixtures (one-step Qiagen and two-step Takara), both showing the ability to differentiate mutated from unmutated amplicons.While the one-step approach allows to slightly shorten the time of analysis, the two-step approach allows for long-term storage of cDNA samples and increases reproducibility over time, since low-concentration RNA samples may not produce consistent results after freeze-thaw cycles 31 .
Concerning the timing and costs, with our laboratory equipment, it is possible to process up to 10 samples every 3 h, starting from the RNA extraction, with a cost of less than € 10 ($ 10.60) per sample.In addition, the choice of a qPCR mixture containing SYBR green dye instead of using a saturating dye (e.g.Eva Green, SYTO9, or LC Green) makes this approach more affordable, also in the perspective of a large-scale screening method.In fact, it has been previously demonstrated that using the Rotor-Gene 6000 instrument, HRM analysis results were effective also using SYBR Green 38,40 .Therefore, this method can be considered a cost-effective approach for the fast screening of VOCs with the aim of facilitating local epidemiological surveillance and limiting the number of samples subjected to WGS.
Nevertheless, the HRM-based approach has some limitations.First, it is important to note that such typing assays may provide atypical results for emerging variants due to new mutations within the primer binding sites, resulting in a decrease in amplification efficiency, and/or between the primers, resulting in a less effective variant recognition.In this case, confirmation or deeper analysis can be performed in selected samples (where the www.nature.com/scientificreports/variant could not be identified) using established WGS approaches, allowing for more targeted use of WGS in epidemiological surveillance of new circulating variants, therefore reducing time and costs for analysis.As new variants emerge, new assays should be designed and optimized before being included in the diagnostic algorithm.Moreover, it is needed to take into account that inconclusive or low-resolution HRM data can be obtained with a poor amplification curve showing Ct > 30 or failing to reach a plateau in the PCR phase 37,38 .To partially overcome this issue, Promja et al. have developed an automated machine-learning web application capable of identifying SARS-CoV-2 variants by interpreting HRM profiles 41 .The authors set the Ct threshold value for variant identification at 33.4, allowing to include samples with low amounts of viral RNA.Finally, it is worth mentioning that the applicability of our method with other qPCR mixtures and instruments different from those used in this work must be optimized, and internal control to establish the HRM range for each assay needs to be included.In summary, this approach could be beneficial in terms of time and costs since it is characterized by modest reagent requirements and utilizes instrumentation already present in many routine clinical and public health laboratories.The development of qPCR-HRM assays has the potential to genetically characterize SARS-CoV-2 VOCs and can be an alternative or an important complement to WGS-based epidemiological surveillance that can directly impact the clinical care of individual patients.Since our approach demonstrated 100% specificity and sensitivity compared with commercial PCR tests for COVID-19, it could be used either to find SARS-CoV-2 positive patients or to monitor already known SARS-CoV-2 variants for epidemiological purposes.Nevertheless, in case of the emergence of new variants, sequencing-based approaches will still be needed to identify new mutations and to allow the design of new qPCR assays.

Ethical statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee (Comitato Etico per la Sperimentazione Umana, CESU) of the University of Urbino Carlo Bo (protocol number n. 46/2022).The approved study protocol included the informed consent forms for the subjects involved.

Identification of polymorphic sites and primer design
Sequences of SARS-CoV-2 reported from countries around the world were randomly downloaded from the EpiCoV database of Global Initiative on Sharing All Influenza Data (GISAID) 8 , the most complete repository of coronavirus-causing COVID-19 genomic data.Selected sequences of each VOC were downloaded from GISAID, loaded on Jalview 42 , and multiple sequence alignment (MSA) was performed using the Multiple Sequence Comparison by Log-Expectation (MUSCLE) 43 .All MSA for each variant was performed against the reference strain Wuhan-H-1 sequence (NCBI GenBank accession number NC_045512.2).For our purpose, only the Spikeencoding region was considered.Among all polymorphisms, those conferring changes in theoretical melting temperatures (Tm) (at least 0.3 °C), potentially allowing the variants discrimination, were identified (Table 1).Amplicon theoretical melting temperatures were determined using Bioedit Sequence Alignment Editor 7.2.5 44 .Primers upstream and downstream of these mutations were designed and checked for specificity using Primer-BLAST 45 (Table 5).

Sample collection
All samples used in this study were surplus material collected for diagnostic purposes during routine examinations.Oro/Nasopharyngeal swabs samples collected in viral transport medium were obtained from Urbino Hospital (ASUR Marche AV1)-Laboratory of Clinical Pathology (Urbino, Italy), Covid-Lab (University of Urbino, Fano, Italy) and Virology Laboratory, Azienda Ospedaliera Ospedali Riuniti di Ancona (Ancona, Italy).A total of 120 samples tested with IVD-certified RT-qPCR kits (Diatheva COVID-19 PCR Kit, Diasorin Simplexa™ COVID-19 Direct Kit, Seegene Allplex™ 2019-nCoV Assay) were selected for the study (106 positive samples and 14 negative samples).The positive samples had a Ct < 30 for all viral target sequences.The VOCs were previously identified in part of these samples through WGS approaches.

RNA purification
RNA from oro/nasopharyngeal swabs was isolated using the Total RNA Purification Kit (Norgen Biotek Corp., Thorold, ON Canada) starting from 250 μl of viral transport media following the Supplementary Protocol for Norgen's Saliva RNA Collection and Preservation Device.

RT-qPCR assays
Two approaches were tested for RT-qPCR: a one-step approach (reverse transcription and PCR amplification in the same tube) and a two-step approach (cDNA synthesis followed by PCR amplification), as described below.In both approaches, at least one sample previously characterized by WGS was always included as internal reference and processed in parallel to the unknown samples.
For the one-step RT-qPCR assays, 5 μl of extracted RNA were added to 35 μl of the reaction mixture containing QuantiNova SYBR Green RT-PCR Master Mix together with QuantiNova SYBR Green RT Mix (QIAGEN, Hilden, Germany) and 400 nM primers.The RT-qPCR reactions were carried out in duplicate in a final volume of 20 µl in a Rotor-Gene 6000 instrument (Corbett Life Science, Mortlake, Australia).The RT step was performed at 50 °C for 10 min followed by a PCR activation step at 95 °C for 2 min and by 40 cycles of amplification (95 °C for 5 s and 60 °C for 20 s).A melting curve analysis at the end of each run from 67-88 °C with a slope of 1 °C/s and 5 s at each temperature was conducted.
For the two-step RT-qPCR assays, the reverse-transcription reaction was prepared from 8 μl of total RNA, using the PrimeScript™ RT Master Mix (Perfect Real Time) (Takara, Kusatsu, Shiga, Japan) according to the manufacturer's instructions.The cDNA synthesis was carried out in a thermal cycler at the following temperatures: 37 °C for 15 min, and 85 °C for 10 s.At the end of the retro-transcription protocol, each sample was diluted 1:2 with RNase-free water.The qPCR was performed using 2 μl of cDNA as template in 38 μl of the reaction mixture containing the TB Green premix ex TaqII Mastermix (Takara Bio Europe, France) and 200 nM primers.The amplification reactions were carried out in duplicate in a final volume of 20 µl in a Rotor-Gene 6000 instrument (Corbett Life Science, Mortlake, Australia), with the same amplification and melting protocols described above.
In addition, in both assays, a duplicate non-template control as negative control was always present.Finally, selected PCR products were analyzed by electrophoresis in a 2.5% agarose gel to evaluate the specificity of amplification and the absence of non-specific products and/or primer dimers.
Assay specificity was experimentally evaluated with clinical specimens of common respiratory pathogens (i.e., Influenza A, Influenza B and RSV A/B).The presence of influenza and RSV viruses in these samples was assessed using the commercial IVD-certified COVID-FLU-RSV RT PCR Detection kit (Diatheva s.r.l., Fano, Italy), following manufacturer's instructions.The kit included an endogenous control (RNase P gene) to monitor the RNA extraction process and the presence of PCR inhibitors.

High-resolution melt (HRM) analysis
The amplicons obtained from one-step or two-step RT-qPCR assays were further subjected to HRM analysis on a Rotor-Gene 6000 instrument.Briefly, HRM was carried out over the range from 67 to 83 °C (for one-step assays) or from 71 to 84 °C (for two-step assays), rising at 0.1 °C/s and waiting for 2 s at each temperature.The gain was optimized before melting on all tubes.For each variant, bins were set to determine the Tm of amplicons.Automated classification of variant of unknown samples was performed by the Rotor-Gene software according to the presence of a derivative peak located within a defined temperature bin.

Analytical sensitivity of the RT-qPCR assays
To evaluate the analytical sensitivity of all primer pairs, we performed one-step RT-qPCR using serial dilutions (from 1 × 10 6 to 1 × 10 2 viral genomes per reaction tube) of SARS-CoV2 synthetic RNA of the reference isolate Wuhan-hu-1 (MN908947.3)(Twist Bioscience, CA, USA).Moreover, to evaluate the potential interference of host RNA as background, 25 ng of human RNA were spiked into each qPCR reaction tube.The curves were obtained from two independent experiments performed in duplicate.

PCR product sequencing
To confirm variant call in samples without WGS data, the PCR products were purified using the MinElute PCR purification kit (Qiagen) and directly sequenced, using both forward and reverse primers, as previously described 46 .The DNA sequencing was performed using the BigDye Terminator v. 1.1 Cycle Sequencing Kit on ABI PRISM 310 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA).Sequences were manually edited, and nucleotide composition was compared with VOCs reference sequences using Bioedit Sequence Alignment Editor 7.2.5.

Figure 1 .
Figure 1.Representative HRM profiles of qPCR assay 1710 (A), SC2DELTAnew (B), OMICRON CA (C), and DEL9 (D).The plot of the negative derivative of fluorescence (dF/dT) vs temperature is shown, and the melting transitions are represented as peaks.Reference samples are evidenced as bold curves, while the negative controls (no template controls) are represented as flat curves.The amplicons containing/not containing the mutation were clearly distinguishable.Melting profiles in panels (A-D) were obtained with one-step RT-qPCR mix.Each sample was tested in duplicate.

Figure 2 .
Figure 2. Hierarchical approach based on qPCR and HRM analysis targeting variable regions in the Spike gene for identification of SARS-CoV-2 VOCs.The names of qPCR assays are boxed.Samples containing VOCs Beta and Gamma (in red) were not available.

Table 2 .
Average values and SD of HRM temperatures for each amplicon obtained with RT-qPCR mix Qiagen.*Unpaired t-test with Welch's correction.

Table 3 .
Average values and SD of HRM temperatures for each amplicon obtained with RT-qPCR mix Takara.*Unpaired t-test with Welch's correction.

Table 4 .
Comparison of HRM analysis and sequencing results (WGS or amplicon sequencing) for SARS-CoV-2 Spike gene mutation detection.